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research on the development of new inference methods and algorithms for wide classes of stochastic models. However, research will be conducted in collaboration with biologically oriented researches allowing
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and significant piece of information to the right point of computation (or actuation) at the correct moment in time. To address this challenge, you will focus on developing theoretical and algorithmic
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and algorithmic foundations for goal-oriented, semantics-aware communication strategies that enable efficient, intelligent, and adaptive information exchange in joint communication and control. In
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to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project includes both
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series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related areas, but application to dynamic systems is
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that yield valid statistical conclusions (inference) on causal effects when using machine learning algorithms and big datasets. The project is part of the research environment Stat4Reg (www.stat4reg.se ), and
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will work in a wide range of projects. The projects collectively show how sustainable forestry research combines advanced monitoring tools, ecological studies, and genetic approaches. They range from
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; they make sense to humans and are accessible to algorithmic techniques while neural models are adaptive and learnable. The aim of this project is to develop models which combine these advantages. The project
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the European Regional Development Fund. Subject description The subject includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals
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Fund. Subject description The subject includes signal processing with emphasis on development and optimization of algorithms for processing single and multi-dimensional signals that are closely related